Case Study Writing Create compelling B2B case studies with research and visuals via inference.sh CLI. Quick Start Requires inference.sh CLI ( infsh ). Get installation instructions: npx skills add inference-sh/skills@agent-tools infsh login

Research the customer's industry

infsh app run tavily/search-assistant --input '{ "query": "SaaS customer onboarding challenges 2024 statistics" }' The STAR Framework Every case study follows: Situation -> Task -> Action -> Result Section Length Content Purpose Situation 100-150 words Who the customer is, their context Set the scene Task 100-150 words The specific challenge they faced Create empathy Action 200-300 words What solution was implemented, how Show your product Result 100-200 words Measurable outcomes, before/after Prove value Total: 800-1200 words. Longer loses readers. Shorter lacks credibility. Structure Template 1. Headline (Lead with the Result) ❌ "How Company X Uses Our Product" ❌ "Company X Case Study" ✅ "How Company X Reduced Onboarding Time by 60% with [Product]" ✅ "Company X Grew Revenue 340% in 6 Months Using [Product]" The headline should be specific, quantified, and state the outcome. 2. Snapshot Box Place at the top for skimmers: ┌─────────────────────────────────────┐ │ Company: Acme Corp │ │ Industry: E-commerce │ │ Size: 200 employees │ │ Challenge: Manual order processing │ │ Result: 60% faster fulfillment │ │ Product: [Your Product] │ └─────────────────────────────────────┘ 3. Situation Who is the customer (industry, size, location) What relevant context existed before the problem 1-2 sentences of company background 4. Task / Challenge Quantify the pain: "spending 40 hours/week on manual data entry" not "had data problems" Show stakes: what would happen if unsolved (lost revenue, churn, missed deadlines) Include a customer quote about the frustration 5. Action / Solution What was implemented (your product/service) Timeline: "deployed in 2 weeks" / "3-month rollout" Key decisions or configurations Why they chose you over alternatives (briefly) 2-3 specific features that addressed the challenge 6. Results Before/after metrics — always quantified Timeframe — "within 3 months" / "in the first quarter" Unexpected benefits beyond the original goal Customer quote about the outcome Metrics That Matter How to Present Numbers ❌ "Improved efficiency" ❌ "Saved time" ❌ "Better results" ✅ "Reduced processing time from 4 hours to 45 minutes (81% decrease)" ✅ "Increased conversion rate from 2.1% to 5.8% (176% improvement)" ✅ "Saved $240,000 annually in operational costs" Metric Categories Category Examples Time Hours saved, time-to-completion, deployment speed Money Revenue increase, cost reduction, ROI Efficiency Throughput, error rate, automation rate Growth Users gained, market expansion, feature adoption Satisfaction NPS change, retention rate, support tickets reduced Data Visualization

Generate a before/after comparison chart

infsh app run infsh/python-executor --input '{ "code": "import matplotlib.pyplot as plt\nimport matplotlib\nmatplotlib.use(\"Agg\")\n\ncategories = [\"Processing Time\", \"Error Rate\", \"Cost per Order\"]\nbefore = [4, 12, 8.50]\nafter = [0.75, 1.5, 2.10]\n\nfig, ax = plt.subplots(figsize=(10, 6))\nx = range(len(categories))\nwidth = 0.35\nax.bar([i - width/2 for i in x], before, width, label=\"Before\", color=\"#ef4444\")\nax.bar([i + width/2 for i in x], after, width, label=\"After\", color=\"#22c55e\")\nax.set_ylabel(\"Value\")\nax.set_xticks(x)\nax.set_xticklabels(categories)\nax.legend()\nax.set_title(\"Impact of Implementation\")\nplt.tight_layout()\nplt.savefig(\"results-chart.png\", dpi=150)\nprint(\"Chart saved\")" }' Customer Quotes What Makes a Good Quote ❌ "We love the product." (vague, could be about anything) ❌ "It's great." (meaningless) ✅ "We went from processing 50 orders a day to 200, without adding a single person to the team." — Sarah Chen, VP Operations, Acme Corp ✅ "Before [Product], our team dreaded Monday mornings because of the report backlog. Now it's automated and they can focus on actual analysis." — Marcus Rodriguez, Head of Analytics, DataCo Quote Placement 1 quote in the Challenge section — about the frustration/pain 1-2 quotes in the Results section — about the outcome/transformation Always attribute: full name, title, company Quote Formatting

"We went from processing 50 orders a day to 200, without adding anyone to the team."

— Sarah Chen, VP Operations, Acme Corp Research Support Finding Industry Context

Industry benchmarks

infsh app run tavily/search-assistant --input '{ "query": "average e-commerce order processing time industry benchmark 2024" }'

Competitor landscape

infsh app run exa/search --input '{ "query": "order management automation solutions market overview" }'

Supporting statistics

infsh app run exa/answer --input '{ "question": "What percentage of e-commerce businesses still use manual order processing?" }' Distribution Formats Format Where Notes Web page /customers/ or /case-studies/ Full version, SEO-optimized PDF Sales team, email attachment Designed, downloadable, gated optional Slide deck Sales calls, presentations 5-8 slides, visual-heavy One-pager Trade shows, quick reference Snapshot + key metrics + quote Social post LinkedIn, Twitter Key stat + quote + link to full Video Website, YouTube Customer interview or animated Social Media Snippet Headline stat + brief context + customer quote + CTA Example: "60% faster order processing. Acme Corp was drowning in manual fulfillment. 4 hours per batch. 12% error rate. After implementing [Product]: 45 minutes per batch. 1.5% errors. 'We went from 50 orders a day to 200 without adding headcount.' — Sarah Chen, VP Ops Read the full story → [link]" Writing Checklist Headline leads with the quantified result Snapshot box with company, industry, challenge, result at top Challenge is quantified, not vague 2-3 specific customer quotes with attribution Before/after metrics with timeframe 800-1200 words total Skimmable (headers, bold, bullet points) Customer approved the final version Visual: at least one chart or before/after comparison Common Mistakes Mistake Problem Fix No specific numbers Reads like marketing fluff Quantify everything All about your product Reads like a sales pitch Story is about the CUSTOMER Generic quotes No credibility Get specific, attributed quotes Missing the "before" No contrast to show impact Always show the starting point Too long Loses reader attention 800-1200 words max No customer approval Legal/relationship risk Always get sign-off